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kevynf

AKBridge MCP Server

by kevynf

index_kq_fashion

Read-onlyIdempotent

Retrieve Keqiao fashion index data and its sub-indices. Select specific metrics like creative talent, new designs, and brand promotion for analysis.

Instructions

柯桥时尚指数 http://ss.kqindex.cn:9559/rinder_web_kqsszs/index/index_page.do :param symbol: choice of {'柯桥时尚指数', '时尚创意指数', '时尚设计人才数', '新花型推出数', '创意产品成交数', '创意企业数量', '时尚活跃度指数', '电商运行数', '时尚平台拓展数', '新产品销售额占比', '企业合作占比', '品牌传播费用', '时尚推广度指数', '国际交流合作次数', '企业参展次数', '外商驻点数量变化', '时尚评价指数'} :type symbol: str :return: 柯桥时尚指数及其子项数据 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo时尚创意指数
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark readOnlyHint=true and idempotentHint=true, so the safe, read-only nature is known. The description adds the return type and source URL, but lacks further behavioral details such as pagination, data update frequency, or any rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured, with a short title line, source URL, and standardized :param:/:return: tags. No redundant or filler content is present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read-only tool with rich annotations, the description provides the parameter choices, return type, and source URL, covering the essential invocation needs. The lack of an output schema is partially mitigated by the explicit DataFrame return type, though column details are not mentioned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has no description for the symbol parameter, but the description provides an exhaustive list of valid choices and its type, which is essential for correct invocation. The meanings are not elaborated beyond the names, but the names are largely self-explanatory, making this a strong compensation for the zero schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states '柯桥时尚指数及其子项数据' indicating it returns the Keqiao Fashion Index and its sub-item data, with a source URL and DataFrame return type. However, there is no explicit verb like 'fetch' or 'retrieve', and it does not differentiate from sibling index tools such as index_kq_fz.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternative index tools. The description lists parameter options and the data source but gives no context for selection or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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